General model selection estimation of a periodic regression with a Gaussian noise
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DOI: 10.1007/s10463-008-0193-1
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References listed on IDEAS
- V. Konev & S. Pergamenshchikov, 2003. "Sequential Estimation of the Parameters in a Trigonometric Regression Model with the Gaussian Coloured Noise," Statistical Inference for Stochastic Processes, Springer, vol. 6(3), pages 215-235, October.
- D. Fourdrinier & S. Pergamenshchikov, 2007. "Improved Model Selection Method for a Regression Function with Dependent Noise," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 59(3), pages 435-464, September.
- Galtchouk, L. & Pergamenshchikov, S., 2006. "Asymptotically efficient estimates for nonparametric regression models," Statistics & Probability Letters, Elsevier, vol. 76(8), pages 852-860, April.
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Cited by:
- E. A. Pchelintsev & S. M. Pergamenshchikov, 2018. "Oracle inequalities for the stochastic differential equations," Statistical Inference for Stochastic Processes, Springer, vol. 21(2), pages 469-483, July.
- Vlad Stefan Barbu & Slim Beltaief & Sergey Pergamenshchikov, 2019. "Robust adaptive efficient estimation for semi-Markov nonparametric regression models," Statistical Inference for Stochastic Processes, Springer, vol. 22(2), pages 187-231, July.
- Evgeny Pchelintsev & Serguei Pergamenshchikov & Maria Leshchinskaya, 2022. "Improved estimation method for high dimension semimartingale regression models based on discrete data," Statistical Inference for Stochastic Processes, Springer, vol. 25(3), pages 537-576, October.
- Evgeny Pchelintsev, 2013. "Improved estimation in a non-Gaussian parametric regression," Statistical Inference for Stochastic Processes, Springer, vol. 16(1), pages 15-28, April.
- Victor, Konev & Serguei, Pergamenchtchikov, 2015. "Robust model selection for a semimartingale continuous time regression from discrete data," Stochastic Processes and their Applications, Elsevier, vol. 125(1), pages 294-326.
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Keywords
Model selection procedure; Periodic regression; Oracle inequality; Non-parametric regression; Improved estimation;All these keywords.
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